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ANOVA of Instream Turbidity Measurements for TMDL Effectiveness Monitoring of Forest

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  032349,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14985) @2003
Authors:   William J. Conroy, Jeffrey C. Barrett
Keywords:   Turbidity, monitoring, best management practices, TMDLs, industrial forests

The purpose of this project was to determine the feasibility of using nephalometric turbidity measurements as a tool for evaluating the effectiveness of best management practices implemented on an industrial forest in Northern California by examining the variances between turbidity readings taken 1) between sub-basins, 2) between rain storm events), 3) between simultaneous samples taken at different channel cross-section positions, and 4) between identically calibrated nephalometers. As expected, there was highly significant variability in turbidity levels 1) between storm runoff events, 2) within storm runoff events, and 4) between sub-basins of a watershed. What was unexpected was finding significant differences between identically calibrated nephalometers, but no significant differences between positions in a single stream channel at the same measurement time. The results of this pilot study have several important implications for using nephalometric turbidity measurements in TMDL effectiveness monitoring programs. Nephalometric turbidity is primarily useful when gross comparisons are required, and have little utility when the exact level of turbidity is being used as a performance standard. Comparisons between studies using turbidity will be questionable because nephalometric turbidity meters can give significantly different turbidity readings. Due to significant differences within and between the factors measured, changes in turbidity levels due to BMP implementation may be very difficult to detect, monitoring programs will require lengthy pre- and post-treatment monitoring periods, and monitoring programs will require a large number of monitoring locations in areas that have highly heterogeneous physical characteristics.

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